Ch 12: extract 3

Why organisms are not machines: three reasons (at least five more to come)

1. On-off

First, a machine is static until switched on, and may be switched off without ceasing to exist. Organisms, as Nicholson points out, much like waterfalls or tornadoes, do not have an off switch.^[1] The very existence of an organism is, from beginning to end, one unceasing flow of matter and energy. For it to stop, even for an instant, would mean immediate death. As J.B.S. Haldane put it, using the image of fire – pure energy – rather than water, ‘a flame is like an animal in that you cannot stop it, examine the parts, and start it again, like a machine. Change is part of its very being.’^[2] As he hints, analysis – examining its supposed ‘parts’ – would stop it and kill it. Yet the biologist endlessly, and for some purposes necessarily, relies on taking slices from the seamless flow of life. Just consider the conventional anatomical techniques (anatomy, the study of living form, literally means ‘cutting up’) for examining nature: dissecting, slicing, desiccating, pickling, staining, fixing, and freezing, not to mention vivisection.^[3] Organisms may be taken apart, but they are not put together; they are not made – they become. And such entities as we can identify (genes, molecules) cannot take precedence over the relationships which go to constitute them.

In biology all is becoming, never just being:

in the biological world, at least – activity and being necessarily presuppose one another. Being is neither ontologically nor temporally prior to activity, as the very existence of living beings is only possible by means of continuous activity.^[4]

No machine model can make sense of this, since a machine must be built before it can be set in motion. This alone should alert us to its misleading nature. The machine, the thing, takes priority over the process: it comes first in time, and its existence grounds what it does. For living beings – perhaps they should be called living ‘becomings’ – this is not the case: they are what they do, and come into being through their very movement. In this they are like streams that flow. Their being, their form, their becoming, is their movement; and their movement is their being.

2. Motion vs stasis

This leads seamlessly to the next obvious distinction. What has to be explained about a machine is how it changes at all. This is because it is a system that exists close to dynamic equilibrium. When power is applied, one otherwise static and self-contained component transmits energy to another static and self-contained component, and so on, in a linear chain. Then it is switched off, and it returns to equilibrium, where it can remain indefinitely.

In an organism, by contrast, what has to be explained is, not how it changes, but how it remains stable, despite constant change on an unimaginable scale. The stable continuance of a stream is owed to change. It depends on the flow of water molecules through it, entering and passing on elsewhere, and if the water ever stopped steadily flowing and replacing itself the stream would cease to exist. In this way, as Nicholson points out, the idea of an organism as a stream of life rather than a machine captures two essential and complementary elements: ‘the continuous exchange of matter that defines metabolism on the one hand, and the stability of form that is maintained in spite of it on the other.’^[5]

If we pay attention to what is disclosed by biological organisms, we cannot but see process and flow at its core. ‘Whatever else organisms may be, what cannot be denied at an ontological level is that they are stable metabolic flows of energy and matter.’^[6] We know this intuitively. Most of the cells in your body were not there a few years ago: the form of the flow has persisted, but its original substance has utterly vanished. As the German poet Novalis observed in the late eighteenth century, ‘there is no doubt that our body is a moulded river’.^[7] But this is not an intuition only. It is the best metaphor we have for the proper physiological understanding of living tissue. John Scott Haldane saw organisms as highly dynamic eddies of matter, which nonetheless had the power to remain stable over time – not things, but stabilised processes: ‘they are constantly taking up and giving off material of many sorts, and their “structure” is nothing but the appearance taken by this flow of material through them.’^[8]

Structure is the static element we illegitimately extrapolate from the flow of time. Individual organisms, and the evolutionary process in which they inhere, are extended in time – not a sequence of timeless structures, without extension, that replace one another. Structure is function once time has been excluded; function is structure once included in time.^[9]

Moreover, in as much as the organism can be said to have ‘fixed’ structures at all, they are themselves as much the result of flow, as the cause of it. Biologist Craig Holdrege gives this thought-provoking example, from human foetal development:

Before the heart has developed walls (septa) separating the four chambers from each other, the blood already flows in two distinct ‘currents’ through the heart. The blood flowing through the right and left sides of the heart do not mix, but stream and loop by each other, just as two currents in a body of water. In the ‘still water zone’ between the two currents, the septum dividing the two chambers forms. Thus the movement of the blood gives the parameters for the inner differentiation of the heart, just as the looping heart redirects the flow of blood.^[10]

Above I mentioned that change in a living organism takes place on an unimaginable scale. Let me give some idea of that scale. There are an estimated 37.2 trillion cells in the human body.^[11] Each one of these cells performs many millions of complex reactions every second.^[12] In doing so the cell does not act atomistically but within complex feedback systems with other cells. Biological enzymes promote extraordinary rates of change. In the absence of catalytic enzymes, the decarboxylation of amino acids would proceed with a typical half-life of about a billion years: in the presence of enzymes these half-lives are reduced to less than a thousandth of a second.^[13] And a single molecule such as carbonic anhydrase – of which the body contains unimaginable numbers – can catalyse upwards of a million reactions per second.^[14] Each protein may combine with ‘several hundred different modifier molecules, leading to practically infinite combinatorial possibilities’ and each ‘protein itself is an infinitesimal point in the vast heaving and churning molecular sea of continual exchange that is the cell’.^[15]

One research team writes that in an organism we see a collaborative process that can be ‘pictured as a table around which decision-makers debate a question and respond collectively to information put to them.’^[16] But if that is the case, we must remember that, as Talbott points out,

the collaborative process mentioned above involves not just one table with ‘negotiators’ gathered around it, but countless tables with countless participants, and with messages flying back and forth in countless patterns as countless ‘decisions’ are made in a manner somehow subordinated to the unity and multidimensioned interests of the organism as a whole.^[17]

The human organism, it is clear, exists in a state of stable, patterned flux that we cannot even begin to conceive.

All living things metabolise, that is to say exist in a constant energetic exchange with their surroundings. The word ‘metabolism’, from Greek metabolē, means simply ‘change’. Homoeostasis, growth, and reproduction are the three most fundamental characteristics of cells and all living things – and they are all processes.^[18] ‘One decisive reason for taking organisms to be processes’, writes Dupré, is that they are

open systems that must constantly exchange energy and matter with their surroundings in order to keep themselves far from equilibrium. The persistence of an organism is dependent on its ability continuously to maintain a low-entropic ‘steady state’ in which there is a perfectly balanced import and export of materials. When this exchange ceases, the steady state is irretrievably lost and the organism succumbs to equilibrium, resulting in death … You can leave your typewriter in an empty loft and return a decade later and start using it again. But if you accidentally leave your hamster in the loft, you will not have a hamster for very long.^[19]

At the cellular level, Dupré points out, ‘the persistence of the human organism over the life cycle requires an almost inconceivably precise balance of division, differentiation and destruction of cells.’^[20] And at the molecular level, according to biochemist Ross Stein, proteins are not inert, but ‘dynamic entities that negotiate complex energy landscapes’.^[21] Biochemistry, the chemistry of life, is endlessly dynamic, changing, creating, repairing, transforming. ‘The great challenge for the life sciences today’, writes Shapiro,

is to understand how all the regulatory processes and control circuits operate to make indescribably complex reproductive, repair and morphogenetic processes come out right in the face of changing circumstances.^[22]

To the left hemisphere’s linear habit of mind, and its predilection for ‘things’, there is something paradoxical about stability depending on change. But the joint action of two forces tending to counteract one another is one of the best recipes for stability, found throughout the natural world: it is the essence of homoeostasis.^[23] Examples are everywhere in animal and human bodies, in the regulation of temperature, blood pressure, muscle tone, hydration, cell renewal, and many, many other equilibria, which are stable because they are dynamic, not static (the balanced functioning of the asymmetrical brain, being, of course, another): they involve the harmony of opposing tendencies. A tightrope walker balances by making and responding to myriad tiny movements in the rope: completely stabilise the rope and the performer falls off. (Equally let it go too slack and the same happens.) The right hemisphere view is more inclusive than that of the left: stability can be explained by dynamism alone, but dynamic processes cannot be explained by static ‘things’ alone.

One very important element in all life is, of course, evolution. Many problems arise from seeing evolution as effectively the replacement of one element (a species) by another: as a chain, not a flow. ‘Organisms do not, of course, evolve’, writes Dupré. ‘Evolution relates to the distribution of the properties of organisms over time.’^[24] Evolution is a flow that seamlessly connects all life. What seem like species are just our way of reifying that flow (‘thingifying’ it) at any one moment in time. As geneticist Charles Birch put it, ‘nuts and bolts cannot evolve! They can only be rearranged.’^[25] Life is not a rearrangement of already known nuts and bolts, but the constant creation of something radically new.

Once one understands that one is dealing with flow, natural selection can be seen for what it is: a stabiliser, not an agent of change. Indeed, and fairly obviously, natural selection is never the originator of change at the gene level; it acts only to stabilise an already existing change. By selecting the most adaptive phenotypes, the lineage is stabilised over longer periods of time.^[26] Equally, as we shall shortly see, genes are not stable elements in the story, unchanging unless by blind accident: they are themselves constantly changing or being changed, in highly adaptive ways.

3. Non-linearity

A serious problem for adherents to the machine model is that, while they are obliged by the model to explain organisms from the bottom up only, the deeper they go the less of anything remotely machine-like can be found. The scarcely material entities that physicists have grappled with over the last hundred years offer little reassurance that, if only we go to a more basic level, we are going to find a mechanism. As the biologists try to account for mind in purely material terms, physicists have increasingly been inclined to account for matter by appealing to mind.

However, long before we get down to the quantum level, things show no signs of getting simpler: they remain stubbornly as complex and animate as we go down in scale.

Here I’d like to pick up the observation that no organism develops as the result of the execution of a sequence of predetermined steps. Each developmental ‘step’ is not simply computable from the immediately preceding one. In a classical mechanism, causation is linear and can be clearly outlined. However, in biological systems, causation tends to follow not straight lines, but spirals, involving recursive loops, and multiple causes leading to multiple effects across a network, with sometimes competing factors cross-regulating one another, reciprocally interacting, and in ways we do not understand taking information from the whole. All this makes the classic idea of a two-element, cause and effect sequence unhelpful. ‘The standard two-event model’, according to philosophers of science Rani Lill Anjum and Stephen Mumford, ‘does not handle this complexity well, offering us just more and more of the same discrete two-events causally related.’^[27] A mechanism, in other words.

The geneticist Philip Gell, speaking about his area of research, considers that ‘the heart of the problem lies in the fact that we are dealing not with a chain of causation but with a network’, something like a spider’s web, in which a perturbation at any point of the web changes the tension of every fibre in it.^[28] Context is everything. Which means we cannot simply account for organisms from the bottom up, but must do so at least as much from the top down. Not to mention from the sides, as in a web. We might be accustomed to thinking of biological processes in the abstract, isolated artificially by our mode of attention. But each element in each process is likely to be involved in several other ‘causative chains’, more like an unimaginably complex piece of choreography, where members of one group pass in and through another, for a while belonging to both or neither – each process having its own apparent end. According to Nobel Prize-winning geneticist Sydney Brenner, development ‘is not a neat, sequential process … It’s everything going on at the same time.’ And, he continues, in words that strike at the core of the reductionist enterprise, ‘there is hardly a shorter way of giving a rule for what goes on than just describing what there is.’^[29]

This puts me in mind of some words of Marcelo Gleiser, here speaking of the whole material world: ‘When it comes to physical reality, there are no final explanations but ever more efficient descriptions.’^[30] Not understanding – not even, necessarily, explanation; but description.

Until recently it was assumed that signalling pathways in cells were linear sequences, beginning from a defined starting point and progressing by an orderly sequence of steps to a defined conclusion. Somehow it was overlooked that each of these theoretically abstractable sequences was in practice interlocked at different points with other dynamically evolving sequences. A team of molecular biologists from Brussels decided to plot the interactions between just four cascades, each consisting of only five steps. The result, as they put it, is a ‘horror graph’ (see Plate 13[a]):

With four cascades of five steps, the number of possible positive and negative interactions is 760. This does not take into account the multiplicity of different isoforms of proteins at the different levels of the cascades, the multiplicity of effects of each intermediate in each cascade, the stimulation by a cascade of the secretion of extracellular signals, or feedback or feedforward controls within cascades. In fact, so many interactions are now described (everything does everything to everything) that it is difficult to reconcile this concept with the known specificity of action of signals in each cell.^[31]

‘Everything does everything to everything’: interlocking, reciprocal and interpenetrating processes on such a scale show chains of causation to provide limited insight into cell responses.

But that’s not all. It’s not just that steps are related in a more complicated fashion than the machine model leads us to assume. It’s that the idea of there being steps at all (even if useful when focussing on the minuscule and the time-sliced) is misleading when looking at the whole over a duration of time. This is an idea that I mentioned in an earlier chapter, and will return to at various points in this book. It might not seem at first sight that significant. I hope to show that it is a crucial insight into what is peculiar about the way we in the West now tend to view the world. It is the difference between a sequence – a concatenation, a chain – and a single, indivisible movement, a flow. Flow is a process: a chain is a series of things, that are static until one is given a push or a pull by the thing next to it. An organism is a flow, and is alive. A machine is a chain, and is dead.

Can one even talk about causation in a flow? There are certainly temporal regularities, but does the earlier part of a stream cause the latter, in any conventional sense? For that, the two parts would have to be distinct entities. Alan Watts describes someone who has never seen a cat, squinting through a crack in a fence, and seeing a cat’s head appear, followed moments later by its tail. The cat turns round and comes back: first the head appears, then the tail. Later he sees another such event, and another. Eventually he draws the conclusion that the event ‘head’ causes the event ‘tail’, which is its invariable effect.^[32] Causation could be seen as an artefact – a useful one – of time-slicing, slicing the flow. (It might be objected that, while it is true that no one part of a waterfall or a tornado causes another, it is surely possible to say that each, as a whole – the waterfall and the tornado – has a cause, or, at any rate, causes. But that depends on seeing the world at large as a collection of things, not processes. For where does the precipitation of rainwater, the configuration of the land, the air pressure, the wind speed that would be said to be their causes begin and end? I appreciate that one argument might be that that is precisely why we need to think in terms of ‘things’; and it’s no doubt one reason why we do. But my claim is not that ‘thing-thinking’ has no uses – just that thinking in that way imports a whole set of assumptions that are, to say the least, open to challenge; and makes it difficult or impossible to see elements of the picture that we would be wrong to ignore.)

Similarly molecules, whether in an organic system or not, are ‘a part of a continuum of relational interactions’, more like a flow than a chain.^[33] Beyond this, we have known since the 1960s that the behaviour of proteins cannot be fully described using linear, classical mechanics; and more recent research even demonstrates quantum entanglement between particles in two wholly distinct (as we would normally think) organisms, widely separated in space. Behaviour at the cellular level requires a quantum mechanical account in order to be understood, even if Newtonian mechanics is for most practical purposes an adequate, if approximate, fit.^[34]

Incidentally, this seems like a good moment to gloss the unfortunate expression ‘quantum mechanics’. After all, I am arguing that the machine model is misleading: what’s achieved by substituting one kind of mechanics – ‘quantum’ – for another – ‘Newtonian’? David Bohm puts it well:

The entire universe must, on a very accurate level, be regarded as a single indivisible unit in which separate parts appear as idealisations permissible only on a classical level of accuracy of description. This means that the view of the world being analogous to a huge machine, the predominant view from the sixteenth to nineteenth centuries, is now shown to be only approximately correct. The underlying structure of matter, however, is not mechanical … This means that the term ‘quantum mechanics’ is very much of a misnomer. It should, perhaps, be called ‘quantum nonmechanics’.^[35]

Or, perhaps even, ‘non-quantum non-mechanics.’ I will discuss the model of quantum mechanics, and the related and even more powerful model, quantum field theory, in Chapter 24. It turns out that not only the word ‘mechanics’, but the word ‘quantum’, while certainly having a meaning, needs significant qualification.

Finally, unlike organisms, machines, including computers, do not operate in Gestalt fashion: when they are engineered so as to give the appearance of doing so – eg, facial recognition software – they do so still via rules and procedures applied to measurements, depending on trawling blindly and laboriously through vast heaps of data, in a process that speaks not of intelligence but its opposite. The linearity of this approach can no more reach the curve of true intelligence than straight lines, however many they be, can describe the circumference of a circle, though they may give the illusion of doing so. According to microbiologist Brian Ford,

the essential processes of cognition, response and decision-making inherent in living cells transcend conventional modelling, and … reveal a level of cellular intelligence that is unrecognized by science and is not amenable to computer analysis …biological systems are non-linear systems that are not amenable to digital modelling. As [the physicist Alex] Hankey has reminded us,^[36] many are founded on unfathomable complexity. ^[37]

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^[1] Nicholson 2018 (153).

^[2] Haldane 1940 (57).

^[3] Dupré & Nicholson 2018 (39).

^[4] Nicholson 2018 (153).

^[5] ibid (149). Cf Schelling 1799b (11: emphasis in original): ‘The chief problem in the philosophy of Nature is not to explain what is active in Nature (for that, being her primary condition, is easily understood), but rather that which is static and permanent. The explanation however lies within that very condition – that whatever is permanent is for Nature the limit-point of her activity. For, given this, Nature restlessly strives against every limitation’ – » Das Hauptproblem der Naturphilosophie ist nicht, das Thätige in der Natur, (denn das ist ihr sehr begreiflich, weil es ihre erste Voraussetzung ist), sondern das Ruhende, Permanente zu erklären. Zu dieser Erklärung aber gelangt sie eben durch jene Voraussetzung, daß das Permanente für die Natur eine Schranke ihrer eignen Thätigkeit sey. Denn, wenn dies ist, so wird die rastlose Natur gegen jede Schranke ankämpfen «.

^[6] Nicholson 2018 (148).

^[7] See Novalis 1967 (541): » Daß unser Körper ein gebildeter Fluß ist, ist wohl nicht zu bezweifeln. «

^[8] JS Haldane 1917 (90).

^[9] Vial de Saint-Bel, a famous veterinary surgeon and anatomist of the eighteenth century, proved mathematically from minute examination of the limb structure of a legendary racehorse, Eclipse, that he must have made certain movements with his legs which nobody could see. ‘Only when instantaneous photography was invented and applied to horse-racing, did these movements actually make their appearance in the photograph of a galloping horse’ (Cook 1902, 127–8).

^[10] Holdrege 2002 (12).

^[11] Bianconi, Piovesan, Facchin et al 2013.

^[12] Alberts, Johnson, Lewis et al 2008.

^[13] Stein 2004. See also Snider & Wolfenden 2000.

^[14] Berg, Tymoczko & Stryer 2002.

^[15] Talbott 2010b (32).

^[16] Levy, Landry & Michnick 2010.

^[17] Talbott 2010b (32–3).

^[18] Anjum & Mumford 2018 (63).

^[19] Dupré & Nicholson 2018 (15).

^[20] Dupré 2017b.

^[21] Stein 2004.

^[22] Shapiro 2013.

^[23] On the ‘stable’/‘static’ distinction in biology, see, eg, Dupré 2014 (15).

^[24] Dupré 2017a.

^[25] Birch 1988.

^[26] Dupré 2017a; Dupré & Nicholson 2018 (35).

^[27] Anjum & Mumford 2018 (65).

^[28] Gell 1984 (186).

^[29] Lewin 1984.

^[30] Gleiser 2014 (185).

^[31] Dumont, Pécasse & Maenhaut 2001 (I owe this example to Talbott 2010b).

^[32] Watts 1989 (30–1). This is something like Hume’s deconstruction of causation as mere repeatedly observed temporal propinquity.

^[33] Stein 2004.

^[34] Szent-Györgyi 1960; Pophristic & Goodman 2001; Yamamoto, Koashi, Ozdemir et al; Shi, Kumar & Lee 2017.

^[35] Bohm 1951: ‘The need for a nonmechanical description’, ch 8, §26 (167). The last two sentences follow on as a footnote at the base of the page.

^[36] Hankey 2015.

^[37] Ford 2017.